Product Stickiness

How to Measure Product Stickiness

Product stickiness is a method to measure user engagement, which is a function of how compelling the product is, in itself, and the frequency at which the end-user engages with the product (or its features).

Simply put, “stickiness” measures how often and how frequently users engage with a company’s product in a specified time frame.

However, the term, “engage”, can be subjective at times, as the management team of each company defines the term at their discretion, which is usually based on their unique business model (and the industry where the company operates in).

Conceptually, the question answered by product stickiness is, “How many users return to engage with a particular product on a regular basis, within a specified time frame.”

For example, a mobile game developer might consider periodic usage, even if checking an app momentarily, as a form of engagement, whereas other digital media companies are more conservative and could perhaps only consider interacting with the product and its features for a predefined period of time to constitute “engagement”.

Products considered to be “sticky” are implied to deliver value to their customers (i.e. positive economic utility); hence, the customers continue to return (i.e. repeat purchases or continuation of subscription plan without cancellation).

All products, irrespective of the industry and success achieved to date, must be tweaked and improved upon to remain ahead of the curve (i.e. continuous improvement).

Product stickiness is thereby a method measure the effectiveness at which a company’s business model can entice frequent usage, contributing toward customer loyalty.

Creating engaging user experiences and improving product features are two common methods to improve the stickiness rate.

How to Calculate Product Stickiness

Sticky products are not used by the customer once in a while, but rather, the product becomes part of a customer’s daily routine with frequent usage, contributing toward improved customer retention.

In order to measure product stickiness, the following metrics are used, most often referred to using acronyms:

• Daily Active Users (DAU) ➝ The number of unique users that interacted with a product (or website) on a daily basis, i.e. 24 hour period.
• Weekly Active Users (WAU) ➝ The number of unique users that interacted with a website (or app) on a weekly basis, i.e. 7 day period.
• Monthly Active Users (MAU) ➝ The number of unique users that interacted with a product, or website, in a particular month, i.e. 30-day period.

One nuance to consider is that the product type dictates which metric to apply.

For instance, DAU is most appropriate for consumer products—such as for social apps—in which daily usage is expected.

On the other hand, for certain B2B SaaS products, WAU is likely the more approproate metric to analyze and benchmark, considering the enterprise client is anticipated to only use the product once per week.

The step-by-step process to calculate product stickiness is as follows:

• Step 1 ➝ Count the Number of Active Users per Day (DAU)
• Step 2 ➝ Calculate Average DAU (Σ DAU ÷ MAU)
• Step 3 ➝ Calculate Total Number of Users Engaged Minimum Once in the Month (MAU)
• Step 4 ➝ Divide Average DAU by MAU

Conversely, rather than using the average DAU, the DAU variable can cover one single day.

However, the average DAU tends to be more practical because the high-level trends and patterns are more easily detectable — but either method can offer useful insights.

In either case, the DAU is measured on a rolling basis, i.e. constantly tracked and updated per day.

^{The Stickiest Mobile Social Apps in the U.S. (Source: a16z + Apptopia)}

Product Stickiness Formula

The DAU/MAU ratio is the fundamental indicator of product stickiness and user engagement.

The formula to calculate product stickiness is the ratio between the product’s daily active users (DAU) to monthly active users (MAU), expressed as a percentage.

Where:

• Daily Active Users (DAU) ➝ The number of unique users engaging with a company’s product on a daily basis.
• Monthly Active Users (MAU) ➝ The number of unique users engaging with a company’s product on a monthly basis.

Conversely, the product stickiness can be measured using the average DAU, which is calculated as the average DAU divided by MAU.

SaaS LTV/CAC Ratio Formula

The customer acquisition strategy of a SaaS company—one of the core components of its business model—is sustainable only if higher retention (and thus, reduced churn) contribute toward an increase in customer lifetime value (CLV.)

While there are plenty of SaaS metrics to analyze the unit economics of a subscription company, the fundamental method used among practitioners is termed the customer lifetime (LTV) to customer acquisition cost (CAC) ratio.

Or, put more concisely, the LTV/CAC ratio, which quantifies the total value collected from the customer divided by the cost of acquiring the customer.

The standard LTV/CAC ratio in the SaaS industry is widely accepted as 3.0x, which tends to be the target at which most SaaS and subscription companies aim for.

Given an LTV/CAC ratio equal to 3.0x, the SaaS company generates $3.00 in lifetime value (LTV) from a customer for each $1.00 spent on acquiring that customer, such as sales and marketing (S&M).

How to Improve Product Stickiness Rate

The underlying factors that directly contribute toward a higher stickiness rate include user experience, user retention, and engagement rate, among others.

Why Does Product Stickiness Matter in the SaaS Industry

The business model inherent to the SaaS industry, inclusive of subscription pricing strategies, is oriented around the continued generation of recurring revenue.

The companies that operate in the SaaS industry and offer subscription-based products can improve upon the long-term viability of their customer acquisition strategies and growth tactics, which improves their revenue growth trajectory and profitability.

By establishing a stream of recurring revenue (or repeat purchases), which are closely intertwined with product stickiness, the outcome is more stability and predictable operating performance.

The formula to calculate the repeat purchase rate is equal to the number of repeat purchase customers (i.e. >1 purchase), divided by the total number of customers.

In particular, an early-stage startup must be growth-oriented, at the expense of reduced profitability, and must strategically allocate most of their time and resources toward implementing initiatives to acquire new customers, conducting market research, and product development to improve their product relative to competing offers (and to meet customer needs).

Therefore, one central theme here is that a company must not become complacent, particularly in competitive markets (i.e. “red ocean strategy”), so continuously collecting customer feedback and compiling data to detect patterns in their spending behavior, including trends, should be conducted while the customer is still, in fact, a customer.

In practice, the mistake made far too common by early-stage startups (and to a much lesser degree, growth stage companies) is to neglect existing customers once acquired and move onward with their plan to expand their scale and achieve more growth.

Customers, however, churn if the value received is not enough—or if a comparable product could deliver the same, if not better, value proposition.

The churn rate measures the rate at which customers decide to discontinue being a source of revenue for a company (i.e. no longer a customer).

The churn rate must stabilize over time as a company refines its customer acquisition strategy and business model. Otherwise, the revenue model is not sustainable in the long haul.

If an early-stage startup’s churn rate seems unsustainable, the startup could perhaps raise more funding from their existing equity investors, assuming the capital contributors trust the founder’s intuition (and the revenue growth and market traction serves as proof that the market demand represents a compelling opportunity).

The inverse of the churn rate is the retention rate, which refers to the percentage of customers who continue to use a company’s products or services across a specified period.

The formula to calculate the retention rate of a company is equal to the difference between the number of customers at the end of the period and the number of new customers at the start of the period, divided by the number of beginning customers.

The retention rate—to reiterate from earlier—is the inverse of the churn rate (or attrition rate), so an alternative option to compute the metric is by subtracting the churn rate from one.

How to Analyze Product Stickiness in SaaS Business Model

Customers churn is an inevitable part of running a SaaS or subscription-based business, of course, irrespective of the perceived value of the product (i.e. external circumstances outside a company’s control can influence customer behavior).

There are certainly times, however, when customer churn is rightfully deserved, and to make matters worse startups often strive to convince churned customers to not abandon the ship.

The critical takeaway here is that a management team fixated on counting the total number of acquired customers, with no consideration toward customer retention, is short-sighted for an early-stage company.

In other words, most startup founders are likely unsure which specific problem in the markets (or society) that their product will fix, or even understand their target customer demographic and end market.

With that said, an early-stage startup that manages to acquire a new customer presents an opportunity to learn and refine the product based on the insights derived.

In contrast, building long-term relations with customers over time, understanding their specific needs, and then either improving an existing product or outright developing an entirely new product based on those market insights is the route to take.

In fact, the loss of a customer can oftentimes be more helpful to a company’s long-term performance, assuming that tangible steps were taken to address the issues that caused the churn.

Sticky products solidify long-term customer relationships, often structured with multi-year contracts with discounted rates (i.e. incentive), encouraging more engagement.

By securing long-term contracts with customers, more opportunities for upselling, cross-selling, and product bundling strategies emerge over the customer lifecycle.

In short, SaaS companies must build trust with their customers in the market—because without strong retention, business strategies and growth tactics become futile (i.e. churn will offset new customer acquisitions).

Product vs. User Stickiness: What is the Difference?

The difference between product stickiness and user stickiness are as follows:

• Product Stickiness ➝ Product stickiness refers to the inherent qualities and characteristics of a product that render it as habit-forming or so deeply integrated into a user’s particular daily routine. A product exhibiting high stickiness possesses compelling attributes that encourage frequent usage from its perceived appeal or utility to customers.
• User Stickiness ➝ User stickiness pertains to the behavioral patterns and habits exhibited by users in relation to a product. Users demonstrate stickiness when they consistently choose to utilize a particular product, even when presented with other, comparable options in the market, or when customers regularly engage with other offerings (or features) within the product ecosystem.

Product Stickiness Calculation Example

Suppose we’re tasked with calculating the DAU/MAU ratio for Meta (Facebook) for fiscal year ending 2023.

User Engagement Data (Fiscal Year, December 2023)

• Facebook Daily Active Users (DAUs) = 2.11 billion
• Facebook Monthly Active Users (MAUs) = 3.07 billion

^{Source: Meta 10-K 2023}

The 2.11 billion in average DAUs recorded illustrates an increase of 6% year-over-year (YoY), whereas the 3.07 billion in MAUs reflect an increase of 3% year-over-year (YoY).

The DAU/MAU ratio of Meta is 68.7%, which we determined by dividing the average DAU by the MAU, as of the end of 2024.

• DAU/MAU Ratio = 2.11 billion ÷ 3.07 billion = 68.7%

In closing, product stickiness is an iterative process that requires the periodic review of a company’s KPIs and collection of user feedback, facilitating data-supported decisions to continuously improve the product’s ability to engage and retain its users base.

^{Meta Platforms — Management Commentary (Source: META 10-K)}